Exceptions Report

Exception Type Service Model Question Name Count
TimeoutError openai gpt-5 question 1

Note: Each unique exception is counted only once. You may encounter repeated exceptions where retries were attempted.

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:34.946681

Details

Interview ID 2252
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.045312

Details

Interview ID 2268
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.050389

Details

Interview ID 2269
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.101798

Details

Interview ID 2278
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.349631

Details

Interview ID 2283
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.354664

Details

Interview ID 2284
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.366324

Details

Interview ID 2286
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.372173

Details

Interview ID 2287
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.377611

Details

Interview ID 2288
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.382684

Details

Interview ID 2289
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.388312

Details

Interview ID 2290
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.393765

Details

Interview ID 2291
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.399888

Details

Interview ID 2292
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.406575

Details

Interview ID 2293
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.416253

Details

Interview ID 2294
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.424962

Details

Interview ID 2295
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.432406

Details

Interview ID 2296
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.439878

Details

Interview ID 2297
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.446868

Details

Interview ID 2298
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.453592

Details

Interview ID 2299
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.459959

Details

Interview ID 2300
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.465819

Details

Interview ID 2301
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.471319

Details

Interview ID 2302
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.476724

Details

Interview ID 2303
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.482392

Details

Interview ID 2304
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.488183

Details

Interview ID 2305
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.494522

Details

Interview ID 2306
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.499887

Details

Interview ID 2307
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.505518

Details

Interview ID 2308
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.511220

Details

Interview ID 2309
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 5.0
 - Agreeableness: 4.75
 - Conscientiousness: 4.5
 - Neuroticism: 1.0
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.476283

Details

Interview ID 2340
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.481431

Details

Interview ID 2341
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.487145

Details

Interview ID 2342
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.492470

Details

Interview ID 2343
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.497404

Details

Interview ID 2344
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.503495

Details

Interview ID 2345
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.508290

Details

Interview ID 2346
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.514349

Details

Interview ID 2347
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.520101

Details

Interview ID 2348
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.525913

Details

Interview ID 2349
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.531752

Details

Interview ID 2350
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.537357

Details

Interview ID 2351
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.543497

Details

Interview ID 2352
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.549848

Details

Interview ID 2353
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.555019

Details

Interview ID 2354
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.561158

Details

Interview ID 2355
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.566706

Details

Interview ID 2356
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.571702

Details

Interview ID 2357
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.578046

Details

Interview ID 2358
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.583149

Details

Interview ID 2359
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.594490

Details

Interview ID 2361
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.600665

Details

Interview ID 2362
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.605590

Details

Interview ID 2363
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.610887

Details

Interview ID 2364
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.617563

Details

Interview ID 2365
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.622907

Details

Interview ID 2366
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.629367

Details

Interview ID 2367
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.636020

Details

Interview ID 2368
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:35.641763

Details

Interview ID 2369
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.867606

Details

Interview ID 2370
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.873906

Details

Interview ID 2371
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.879501

Details

Interview ID 2372
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.887033

Details

Interview ID 2373
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.892937

Details

Interview ID 2374
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.901274

Details

Interview ID 2375
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.907220

Details

Interview ID 2376
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.912710

Details

Interview ID 2377
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.919087

Details

Interview ID 2378
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.925012

Details

Interview ID 2379
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.931323

Details

Interview ID 2380
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.937358

Details

Interview ID 2381
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.942907

Details

Interview ID 2382
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.948640

Details

Interview ID 2383
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.953820

Details

Interview ID 2384
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.959425

Details

Interview ID 2385
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.965583

Details

Interview ID 2386
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.971424

Details

Interview ID 2387
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.976359

Details

Interview ID 2388
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.981886

Details

Interview ID 2389
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.988123

Details

Interview ID 2390
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.993644

Details

Interview ID 2391
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:52.999430

Details

Interview ID 2392
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:53.005192

Details

Interview ID 2393
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:53.010268

Details

Interview ID 2394
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:53.016074

Details

Interview ID 2395
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:53.022563

Details

Interview ID 2396
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:53.027550

Details

Interview ID 2397
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:53.033194

Details

Interview ID 2398
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:53.039399

Details

Interview ID 2399
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 4.75
 - Conscientiousness: 3.5
 - Neuroticism: 2.75
 - Openness: 4.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.025081

Details

Interview ID 2430
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.029789

Details

Interview ID 2431
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.036608

Details

Interview ID 2432
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.042255

Details

Interview ID 2433
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.048398

Details

Interview ID 2434
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.106381

Details

Interview ID 2435
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.106661

Details

Interview ID 2436
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.106858

Details

Interview ID 2437
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.107042

Details

Interview ID 2438
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.133056

Details

Interview ID 2439
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.133600

Details

Interview ID 2440
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.133810

Details

Interview ID 2441
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.133993

Details

Interview ID 2442
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.134184

Details

Interview ID 2443
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.134552

Details

Interview ID 2444
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.134877

Details

Interview ID 2445
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.135060

Details

Interview ID 2446
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.135231

Details

Interview ID 2447
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.135401

Details

Interview ID 2448
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.135735

Details

Interview ID 2449
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.139540

Details

Interview ID 2450
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.146081

Details

Interview ID 2451
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.151401

Details

Interview ID 2452
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.158409

Details

Interview ID 2453
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.163403

Details

Interview ID 2454
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.168708

Details

Interview ID 2455
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.174237

Details

Interview ID 2456
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.180298

Details

Interview ID 2457
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.185857

Details

Interview ID 2458
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.191290

Details

Interview ID 2459
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:53.784862

Details

Interview ID 2460
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:53.785176

Details

Interview ID 2461
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:53.785375

Details

Interview ID 2462
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:53.785569

Details

Interview ID 2463
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:53.785746

Details

Interview ID 2464
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:53.785921

Details

Interview ID 2465
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:53.786102

Details

Interview ID 2466
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:53.786280

Details

Interview ID 2467
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.073927

Details

Interview ID 2468
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.074220

Details

Interview ID 2469
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.074466

Details

Interview ID 2470
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.074681

Details

Interview ID 2471
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.074865

Details

Interview ID 2472
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.075055

Details

Interview ID 2473
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.075239

Details

Interview ID 2474
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.075412

Details

Interview ID 2475
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.075621

Details

Interview ID 2476
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.075807

Details

Interview ID 2477
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.075979

Details

Interview ID 2478
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.076152

Details

Interview ID 2479
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.076326

Details

Interview ID 2480
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.076754

Details

Interview ID 2481
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.076947

Details

Interview ID 2482
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.077160

Details

Interview ID 2483
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.077403

Details

Interview ID 2484
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.077588

Details

Interview ID 2485
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.077764

Details

Interview ID 2486
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.077941

Details

Interview ID 2487
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.078120

Details

Interview ID 2488
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.078296

Details

Interview ID 2489
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 1.0
 - Agreeableness: 3.5
 - Conscientiousness: 5.0
 - Neuroticism: 2.25
 - Openness: 4.5

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.973969

Details

Interview ID 2520
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.974293

Details

Interview ID 2521
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.974552

Details

Interview ID 2522
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.974775

Details

Interview ID 2523
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.975019

Details

Interview ID 2524
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.975216

Details

Interview ID 2525
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.975399

Details

Interview ID 2526
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.975578

Details

Interview ID 2527
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:36.975773

Details

Interview ID 2528
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.179523

Details

Interview ID 2529
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.179823

Details

Interview ID 2530
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.180025

Details

Interview ID 2531
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.180199

Details

Interview ID 2532
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.180377

Details

Interview ID 2533
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.180547

Details

Interview ID 2534
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.180750

Details

Interview ID 2535
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.180925

Details

Interview ID 2536
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.181125

Details

Interview ID 2537
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.181491

Details

Interview ID 2538
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.181705

Details

Interview ID 2539
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.181875

Details

Interview ID 2540
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.182032

Details

Interview ID 2541
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.182185

Details

Interview ID 2542
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.182336

Details

Interview ID 2543
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.182487

Details

Interview ID 2544
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.182657

Details

Interview ID 2545
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.182806

Details

Interview ID 2546
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.182954

Details

Interview ID 2547
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.183145

Details

Interview ID 2548
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.183313

Details

Interview ID 2549
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.876627

Details

Interview ID 2550
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.877051

Details

Interview ID 2551
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.877576

Details

Interview ID 2552
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.877866

Details

Interview ID 2553
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.878069

Details

Interview ID 2554
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.878280

Details

Interview ID 2555
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.878454

Details

Interview ID 2556
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.878640

Details

Interview ID 2557
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.878864

Details

Interview ID 2558
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.879097

Details

Interview ID 2559
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.879301

Details

Interview ID 2560
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.879494

Details

Interview ID 2561
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.879676

Details

Interview ID 2562
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.879887

Details

Interview ID 2563
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.880067

Details

Interview ID 2564
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.880255

Details

Interview ID 2565
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.880421

Details

Interview ID 2566
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.880590

Details

Interview ID 2567
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.880766

Details

Interview ID 2568
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.881199

Details

Interview ID 2569
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:54.881521

Details

Interview ID 2570
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.096912

Details

Interview ID 2571
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.101441

Details

Interview ID 2572
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.101701

Details

Interview ID 2573
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.101878

Details

Interview ID 2574
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.102046

Details

Interview ID 2575
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.102209

Details

Interview ID 2576
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.102388

Details

Interview ID 2577
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.102566

Details

Interview ID 2578
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.102744

Details

Interview ID 2579
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 2.25
 - Conscientiousness: 2.5
 - Neuroticism: 1.5
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.840997

Details

Interview ID 2610
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.841282

Details

Interview ID 2611
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.841468

Details

Interview ID 2612
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.841640

Details

Interview ID 2613
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.841810

Details

Interview ID 2614
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.842021

Details

Interview ID 2615
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.842188

Details

Interview ID 2616
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.842359

Details

Interview ID 2617
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.842559

Details

Interview ID 2618
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.842724

Details

Interview ID 2619
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.842884

Details

Interview ID 2620
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.843044

Details

Interview ID 2621
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.843216

Details

Interview ID 2622
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.843379

Details

Interview ID 2623
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.843822

Details

Interview ID 2624
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.843998

Details

Interview ID 2625
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.844170

Details

Interview ID 2626
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.917878

Details

Interview ID 2627
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.924952

Details

Interview ID 2628
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.925224

Details

Interview ID 2629
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.925491

Details

Interview ID 2630
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.925665

Details

Interview ID 2631
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.925832

Details

Interview ID 2632
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.925990

Details

Interview ID 2633
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.926151

Details

Interview ID 2634
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.926307

Details

Interview ID 2635
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.926463

Details

Interview ID 2636
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.926615

Details

Interview ID 2637
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.926773

Details

Interview ID 2638
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.926925

Details

Interview ID 2639
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.102923

Details

Interview ID 2640
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.103091

Details

Interview ID 2641
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.103267

Details

Interview ID 2642
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.103442

Details

Interview ID 2643
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.103724

Details

Interview ID 2644
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.104146

Details

Interview ID 2645
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.104358

Details

Interview ID 2646
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.104784

Details

Interview ID 2647
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.104963

Details

Interview ID 2648
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.105120

Details

Interview ID 2649
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.105276

Details

Interview ID 2650
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.105431

Details

Interview ID 2651
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.105586

Details

Interview ID 2652
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.105744

Details

Interview ID 2653
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.105898

Details

Interview ID 2654
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.106058

Details

Interview ID 2655
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.106208

Details

Interview ID 2656
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.106359

Details

Interview ID 2657
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.106525

Details

Interview ID 2658
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.106694

Details

Interview ID 2659
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.106855

Details

Interview ID 2660
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.107008

Details

Interview ID 2661
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.107163

Details

Interview ID 2662
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.107327

Details

Interview ID 2663
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.107478

Details

Interview ID 2664
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.107631

Details

Interview ID 2665
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.107783

Details

Interview ID 2666
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.107938

Details

Interview ID 2667
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.108095

Details

Interview ID 2668
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.108250

Details

Interview ID 2669
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.0
 - Agreeableness: 4.25
 - Conscientiousness: 1.75
 - Neuroticism: 4.75
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.927092

Details

Interview ID 2700
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.927250

Details

Interview ID 2701
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.927404

Details

Interview ID 2702
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.927564

Details

Interview ID 2703
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.927720

Details

Interview ID 2704
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.927876

Details

Interview ID 2705
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.928074

Details

Interview ID 2706
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.928231

Details

Interview ID 2707
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.928392

Details

Interview ID 2708
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.928559

Details

Interview ID 2709
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.928749

Details

Interview ID 2710
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.929090

Details

Interview ID 2711
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.929248

Details

Interview ID 2712
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.929406

Details

Interview ID 2713
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.929560

Details

Interview ID 2714
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.929717

Details

Interview ID 2715
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.929878

Details

Interview ID 2716
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.930037

Details

Interview ID 2717
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.930242

Details

Interview ID 2718
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.930406

Details

Interview ID 2719
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.930568

Details

Interview ID 2720
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.930725

Details

Interview ID 2721
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.930883

Details

Interview ID 2722
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.931038

Details

Interview ID 2723
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.931189

Details

Interview ID 2724
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.931338

Details

Interview ID 2725
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.931497

Details

Interview ID 2726
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.931653

Details

Interview ID 2727
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.931807

Details

Interview ID 2728
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:37.931961

Details

Interview ID 2729
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.747406

Details

Interview ID 2730
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.747703

Details

Interview ID 2731
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.747884

Details

Interview ID 2732
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.748101

Details

Interview ID 2733
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.748269

Details

Interview ID 2734
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.748432

Details

Interview ID 2735
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.748587

Details

Interview ID 2736
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.748752

Details

Interview ID 2737
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.748918

Details

Interview ID 2738
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.749072

Details

Interview ID 2739
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.749230

Details

Interview ID 2740
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.749380

Details

Interview ID 2741
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.749536

Details

Interview ID 2742
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.749713

Details

Interview ID 2743
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.749924

Details

Interview ID 2744
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.750124

Details

Interview ID 2745
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.750298

Details

Interview ID 2746
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.753554

Details

Interview ID 2747
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.758811

Details

Interview ID 2748
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.759010

Details

Interview ID 2749
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.759201

Details

Interview ID 2750
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.759353

Details

Interview ID 2751
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.759517

Details

Interview ID 2752
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.759670

Details

Interview ID 2753
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.759824

Details

Interview ID 2754
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.759967

Details

Interview ID 2755
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.760108

Details

Interview ID 2756
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.760438

Details

Interview ID 2757
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.760586

Details

Interview ID 2758
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.760731

Details

Interview ID 2759
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.25
 - Agreeableness: 3.5
 - Conscientiousness: 1.75
 - Neuroticism: 2.0
 - Openness: 4.75

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.021080

Details

Interview ID 2790
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.021358

Details

Interview ID 2791
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.021541

Details

Interview ID 2792
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.021710

Details

Interview ID 2793
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.021873

Details

Interview ID 2794
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.022030

Details

Interview ID 2795
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.022210

Details

Interview ID 2796
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.022367

Details

Interview ID 2797
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.022520

Details

Interview ID 2798
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.022674

Details

Interview ID 2799
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.022827

Details

Interview ID 2800
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.022981

Details

Interview ID 2801
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.023303

Details

Interview ID 2802
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.023468

Details

Interview ID 2803
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.023631

Details

Interview ID 2804
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.023793

Details

Interview ID 2805
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.023950

Details

Interview ID 2806
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.024104

Details

Interview ID 2807
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.024259

Details

Interview ID 2808
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.024410

Details

Interview ID 2809
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.024575

Details

Interview ID 2810
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.024734

Details

Interview ID 2811
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.024893

Details

Interview ID 2812
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.025046

Details

Interview ID 2813
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.025202

Details

Interview ID 2814
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.025355

Details

Interview ID 2815
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.025510

Details

Interview ID 2816
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.025664

Details

Interview ID 2817
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.025817

Details

Interview ID 2818
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:39.025969

Details

Interview ID 2819
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.760891

Details

Interview ID 2820
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.761049

Details

Interview ID 2821
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.761204

Details

Interview ID 2822
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.761512

Details

Interview ID 2823
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.762365

Details

Interview ID 2824
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.762666

Details

Interview ID 2825
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.762866

Details

Interview ID 2826
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.763044

Details

Interview ID 2827
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.763332

Details

Interview ID 2828
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.763664

Details

Interview ID 2829
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.763871

Details

Interview ID 2830
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.764041

Details

Interview ID 2831
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.764202

Details

Interview ID 2832
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.764359

Details

Interview ID 2833
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.764523

Details

Interview ID 2834
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.764685

Details

Interview ID 2835
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.764837

Details

Interview ID 2836
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.764982

Details

Interview ID 2837
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.765133

Details

Interview ID 2838
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.765299

Details

Interview ID 2839
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.765467

Details

Interview ID 2840
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.765617

Details

Interview ID 2841
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.765770

Details

Interview ID 2842
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.765916

Details

Interview ID 2843
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.766062

Details

Interview ID 2844
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.767908

Details

Interview ID 2845
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.768101

Details

Interview ID 2846
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.768255

Details

Interview ID 2847
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.768409

Details

Interview ID 2848
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:55.768568

Details

Interview ID 2849
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 2.5
 - Agreeableness: 3.25
 - Conscientiousness: 2.75
 - Neuroticism: 3.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.504972

Details

Interview ID 2880
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.505400

Details

Interview ID 2881
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.505687

Details

Interview ID 2882
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.505887

Details

Interview ID 2883
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.506070

Details

Interview ID 2884
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.506670

Details

Interview ID 2885
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.506915

Details

Interview ID 2886
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.507108

Details

Interview ID 2887
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.507280

Details

Interview ID 2888
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.507441

Details

Interview ID 2889
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.507841

Details

Interview ID 2890
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.508193

Details

Interview ID 2891
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.515505

Details

Interview ID 2892
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.515783

Details

Interview ID 2893
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.516099

Details

Interview ID 2894
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.516281

Details

Interview ID 2895
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.516454

Details

Interview ID 2896
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.516622

Details

Interview ID 2897
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.516785

Details

Interview ID 2898
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.517307

Details

Interview ID 2899
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.517649

Details

Interview ID 2900
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.517936

Details

Interview ID 2901
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.518125

Details

Interview ID 2902
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.518288

Details

Interview ID 2903
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.518447

Details

Interview ID 2904
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.518603

Details

Interview ID 2905
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.518758

Details

Interview ID 2906
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.518916

Details

Interview ID 2907
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.519079

Details

Interview ID 2908
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:40.519241

Details

Interview ID 2909
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.325375

Details

Interview ID 2910
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.325706

Details

Interview ID 2911
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.325893

Details

Interview ID 2912
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.326113

Details

Interview ID 2913
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.326279

Details

Interview ID 2914
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.326444

Details

Interview ID 2915
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation.
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.326608

Details

Interview ID 2916
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.326772

Details

Interview ID 2917
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.326939

Details

Interview ID 2918
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.327103

Details

Interview ID 2919
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.327257

Details

Interview ID 2920
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.327671

Details

Interview ID 2921
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.327957

Details

Interview ID 2922
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.328335

Details

Interview ID 2923
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.328524

Details

Interview ID 2924
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.328700

Details

Interview ID 2925
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.328879

Details

Interview ID 2926
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.329042

Details

Interview ID 2927
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.329204

Details

Interview ID 2928
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.329368

Details

Interview ID 2929
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.329551

Details

Interview ID 2930
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.329724

Details

Interview ID 2931
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.329889

Details

Interview ID 2932
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.330043

Details

Interview ID 2933
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.330210

Details

Interview ID 2934
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.330373

Details

Interview ID 2935
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.330586

Details

Interview ID 2936
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.330751

Details

Interview ID 2937
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.330950

Details

Interview ID 2938
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:10:00.331114

Details

Interview ID 2939
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: Compressible Packing Cubes, and a description: Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.0
 - Agreeableness: 3.5
 - Conscientiousness: 3.25
 - Neuroticism: 2.5
 - Openness: 4.0

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.327531

Details

Interview ID 2970
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.327824

Details

Interview ID 2971
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.328013

Details

Interview ID 2972
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.328188

Details

Interview ID 2973
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.328355

Details

Interview ID 2974
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.328515

Details

Interview ID 2975
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.328676

Details

Interview ID 2976
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.328842

Details

Interview ID 2977
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.329008

Details

Interview ID 2978
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.329179

Details

Interview ID 2979
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.329338

Details

Interview ID 2980
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.329495

Details

Interview ID 2981
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.329836

Details

Interview ID 2982
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.344241

Details

Interview ID 2983
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.344649

Details

Interview ID 2984
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.345040

Details

Interview ID 2985
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.345264

Details

Interview ID 2986
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.345424

Details

Interview ID 2987
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.345582

Details

Interview ID 2988
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.345863

Details

Interview ID 2989
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.346136

Details

Interview ID 2990
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.346334

Details

Interview ID 2991
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.346550

Details

Interview ID 2992
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.346774

Details

Interview ID 2993
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.347006

Details

Interview ID 2994
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I find this product advertisement to be persuasive..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.347161

Details

Interview ID 2995
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This is an effective advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.347326

Details

Interview ID 2996
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I would purchase this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.347573

Details

Interview ID 2997
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    Overall, I like this product advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.348010

Details

Interview ID 2998
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    This advertisement has made me more interested in the product..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError

Exception Details

Question name: question
TimeoutError

Error Summary

Exception TimeoutError()
Model gpt-5
Question question (linear_scale)
Time 2025-08-17T02:09:41.348182

Details

Interview ID 2999
Question name question
Question type linear_scale
User Prompt
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    I am interested in learning more about this product after seeing this advertisement..
    
    The ad includes three images:
    
    1. 
    2. 
    3. 
    
    A a title: The RIMOWA Original, and a description: Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence..
    

1 : Strongly disagree

2 : Disagree

3 : Neither agree nor disagree

4 : Agree

5 : Strongly agree

Only 1 option may be selected.

Respond only with the code corresponding to one of the options. E.g., "1" or "5" by itself.

After the answer, you can put a comment explaining why you chose that option on the next line.
Scenario None
Agent None
System Prompt
***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25
Inference service openai
Model name gpt-5
Model parameters Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
Raw model response
No raw model response available.
Generated token string
No raw model response available.

Code to reproduce error

from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
    Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement: 
    {{ statement }}.
    
    The ad includes three images:
    
    1. {{ image_1 }}
    2. {{ image_2 }}
    3. {{ image_3 }}
    
    A a title: {{ title }}, and a description: {{ description }}.
    """, question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.

Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.

**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.

**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:

1. **Extraversion**:
   - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
   - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
   - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
   - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
   - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
   - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
   - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
   - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
   - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
   - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.

**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.

**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.

Your personality profile is characterized by:
 - Extraversion: 3.5
 - Agreeableness: 2.75
 - Conscientiousness: 2.25
 - Neuroticism: 2.75
 - Openness: 3.25

""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()

Traceback

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
    return await fut
           ^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
    response = await client.chat.completions.create(**params)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
    return await self._post(
           ^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
    return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
    response = await self._client.send(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
    response = await self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
    response = await self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
    response = await self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
    response = await transport.handle_async_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
    resp = await self._pool.handle_async_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
    raise exc from None
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
    response = await connection.handle_async_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
    return await self._connection.handle_async_request(request)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
    raise exc
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
    ) = await self._receive_response_headers(**kwargs)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
    event = await self._receive_event(timeout=timeout)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
    data = await self._network_stream.read(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
    return await self._stream.receive(max_bytes=max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
    data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
    data = await self.transport_stream.receive()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
    await self._protocol.read_event.wait()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
    await fut
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
    yield self  # This tells Task to wait for completion.
    ^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
    future.result()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
    raise self._make_cancelled_error()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
    await invigilator.async_answer_question()
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
    agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
    return await self.model.async_get_response(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
    await self._async_get_intended_model_call_outcome(**params)
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
    response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
    async with timeouts.timeout(timeout):
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
    raise TimeoutError from exc_val
TimeoutError